Objectives:Brain mechanisms underlying executive processes are regulated by circadian and sleep homeostatic processes. Furthermore, during sleep deprivation (SD), cognitive performance and neural responses are differentially modulated by a clock gene PERIOD3 polymorphism. Here, we investigated interindividual differences on executive brain responses under SD. Critically, we focused on the circadian evening wake maintenance zone (WMZ), a key time-point for sleep-wake regulation. Methods:Thirty healthy young volunteers, genotyped for the PER3 polymorphism (10 PER3 5/5;20 PER3 4/4 homozygotes), underwent42-h SD under constant routine conditions. They performed a 3-back working memorytask in 13successivefMRI sessions. To compare neural activity in the WMZ before and during SD, sessions were realigned according to individual dim light melatonin onset. Results:We tested for a group (PER3 5/5>PER3 4/4) by session effect (WMZ before vs. during SD). From the first evening WMZ(i.e. during a normal waking day) to the second (i.e. following 40h of continuous waking), PER3 5/5 individuals relative toPER3 4/4 showed significantly larger increase in responsesin the left mid-cingulate, bilateral precuneus and thalamus. Interestingly, these regions are involved in executive processes and arousal regulation (thalamus). Conclusions:These results show that the strong circadian wake-maintenance signal depends on sleep pressure, in a PER3-genotype dependent manner. Interestingly, pronounced genotype differences wereobserved in the thalamus, an area that compensates potential lower cortical activity under SD. [less ▲]

It is well established that cognition shows daily fluctuations with changes in circadian phase and sleep pressure. The physiological impact of season changes, which is well characterized in animals ... [more ▼]

It is well established that cognition shows daily fluctuations with changes in circadian phase and sleep pressure. The physiological impact of season changes, which is well characterized in animals, remains largely unexplored in human. Here we investigated the impact of seasonal variation on human cognitive brain function. This cross-sectional study,conducted in Liège (Belgium),spanned from May 2010 to October 2011. Following 8h in-lab baseline night of sleep, 30 volunteers (age 20.9+1.5; 15F)spent 42h awake under constant routine conditions(<5lux, semi-recumbent position, no time-cues). After12h recovery night, they underwent15minfMRI recording while performing a working memory 3-back task (3b) and a letter detection 0-back task (0b). Thus, fMRI data were acquired when volunteers had been in isolation under controlled conditionsfor 63h. Executive brain responses were isolated by subtracting 0b activity from 3b responses (3b>0b).Analysis tested seasonal influence on executive brain responses at the random effects level, using a phasoranalysis across the year.Inferences were conducted at p<0.05, after correction for multiple comparisons over a priori small volume of interest. Significanteffects of season on executive responses were detected inmiddle frontal and frontopolarregions, insula, and thalamus, with a maximum response at the end of summer and a minimum response at the end of winter.These brain areas are key regions for executive control and alertness. These results constitute the first demonstration that seasonality directly impacts on human cognitive brain functions. [less ▲]

Maintaining optimal performance during a working memory task requires not only to detect target items but also to discard fillers. Following signal detection theory, the ability to discriminate target ... [more ▼]

Maintaining optimal performance during a working memory task requires not only to detect target items but also to discard fillers. Following signal detection theory, the ability to discriminate target from non-target stimuli is estimated by d prime (d'). Here we assessed whether d' was modulated by the oscillating circadian signal during a 42-hour constant routine while participants performed 13 sessions of auditory 3-back task. We also tested whether the individual vulnerability to sleep loss predicted by the PERIOD3 gene polymorphism would influence this cognitive modulation imposed by sleep/wake regulation. From a sample of about 400 screened volunteers, thirty-five healthy young volunteers (age 19-26; 17 females) were recruited based on the PER3 polymorphism (twelve 5/5 and twenty-three 4/4 homozygotes). A linear mixed model tested on d’ the effect of circadian rhythmicity (based on melatonin level) and PER3 polymorphism. Given that 3back sessions were not administered at equidistant points, we used ranges to center each individual performance on dim light melatonin onset (DLMO). Analyses on d’ showed an effect of circadian oscillation (F(12,302) = 16.05, p< 0.0001), but also an interaction between gene and circadian oscillation (F(12,302)=1,88, p = 0.0362). This interaction was mainly characterized by a worst d’ in PER35/5subjects in the range covering a period between 21 and 23 hours after the DLMO (W=47; p = 0.0426). These results showed that circadian rhythm influence the discriminative ability under constant routine condition. Interestingly, we observed a better performance in PER34/4in the phase preceding the DLMO, but only in situation of high sleep pressure. Those results show that discriminative ability is differently affect by sleep homeostasis in PER3 polymorphism at the same circadian phase. We interpret this as a bigger vulnerability to sleep loss in PER35/5individuals in the period just before the wake maintenance zone. [less ▲]

Introduction & Objectives Human sleep and wake EEG oscillations are modulated by complex non-additive interaction between homeostatic and circadian processes. Quantitative analysis of EEG data, during extended wakefulness, indicate that its frequency-specificity is influenced by both factors, such that low-frequencies (<8Hz) increase with time spent awake (1), thus more homeostatically-driven, while alpha activity undergoes a clear circadian modulation (2). Interindividual differences in sleep-wake regulation in young volunteers are associated with the variable-number tandem-repeat (VNTR) polymorphism in the coding region of the circadian clock gene PERIOD3 (PER3). Individuals homozygous for the longer allele of PER3 (PER35/5) were reported to generate more slow wave activity during NREM sleep and theta activity during wakefulness, relative to individuals with the shorter allele (PER34/4). However, the phase and amplitude of circadian markers do not differ between these genotypes (3). Here we tested the hypothesis if fluctuations in the dynamics of waking EEG frequency-specificity are modulated by a polymorphism in the clock gene PER3, under 42h of sustained wakefulness. Materials and Methods Population. A total of 400 young men and women were recruited, from whom DNA samples and questionnaire data were collected. On the basis of their PER3 polymorphism, 35 healthy young volunteers (age: 19-26 y; 17 females) were recruited, out of which twelve were PER35/5 and twenty-three PER34/4 homozygotes, and matched by age, gender, level of education, chronotype and IQ at the group level. Study protocol. The laboratory part of this study began in the evening of day 1 until day 5 (Fig. 1). During the first 2 nights (habituation and baseline), volunteers followed one out of two possible sleep-wake schedules (00:00-08:00 or 01:00-09:00). Thereafter, participants underwent approximately 42 hours of sustained wakefulness under constant routine (CR) conditions (semi-recumbent position, dim light <5 lux, no time-of-day information), and a subsequent recovery sleep episode. EEG recordings. Continuous EEG measurements with 9 EEG channels (F3, Fz, F4, C3, Cz, C4, Pz, O1, O2) were performed throughout the CR. Waking EEG was recorded every 2-h, during a modified version of the Karolinska Drowsiness Test (KDT) (4). Data presented here pertain to the last 60-sec of KDT, during which subjects were instructed to relax, to fixate a dot displayed on a screen ca. 75cm and to try to suppress blinks. After re-referencing to mean mastoids, recordings were scored using Rechtschaffen criteria. The 1-min EEGs during the KDT were manually and visually scored for artifacts (eye blinks, body movements, and slow eye movements) offline by 2 independent observers. The absolute EEG power density was then calculated for artifact-free 2-s epochs in the frequency range of 0.5 to 20 Hz , overlapping by 1 second using the pwelch function in MATLAB (7.5.0). For data reduction, power density of artifact-free 2-s epochs was averaged over 20-s epochs. Statistics. Waking EEG delta (0.75-4.5Hz), theta (4.75-7.75Hz) and alpha (8-12.0Hz) power density computed on Central derivation (Cz) were analyzed with a mixed-model analysis of variance (PROC Mixed), with main factors “elapsed time awake” and “genotype” (PER34/4 and PER35/5), and the interaction of these two factors. All p-values derived from r-ANOVAs were based on Huynh-Feldt's (H-F) corrected degrees of freedom (p<0.05). Multiple comparisons were performed using Tukey-Kramer test. Theoretical coefficients for the homeostatic sleep pressure (derived from a quasi-linear function) and the circadian oscillation (24-hour period sine wave) were used in a multiple regression model to predict delta, theta and alpha activity during the CR. Prior to multiple regression analysis, data were normalized according to PROC Transreg, in order to derive the best normalization method for linear and non-linear datasets. Results. Delta activity Analysis of delta activity yielded a significant main effect of “elapsed time awake” (F=5.31; p < 0.0001), albeit no significant effects for “genotype” (F=0.01; p = 0.94) nor for the interaction of these factors (F=0.85; p = 0.65). The multiple regression model revealed a significant regression (R² = 0.0433 Adj. R² = 0.0404; F = 15.24; p <0.0001), for the homeostat (p < 0.0001 ) and circadian (p = 0.0006) coefficients. Theta activity Analysis of theta activity yielded a significant main effect of “elapsed time awake” (F= 12.2; p < 0.0001), although no significant effects for “genotype” (F= 0.1; p = 0.70) nor for the interaction of these factors (F= 0.67; p = 0.86). The multiple regression model revealed a significant regression (R²= 0.072 Adj. R² =0.069; F= 26.36; p <0.0001), for the homeostat (p < 0.0001 ) and circadian (p < 0.0001 ) coefficients. Alpha activity Analysis of alpha activity yielded a significant main effect of “elapsed time awake”(F=3.43; p < 0.0001), although no significant effects for “genotype” (F = 0.01; p = 0.92) nor for the interaction of these factors (F= 1.23; p = 0.22). The multiple regression model revealed a significant regression (R²=0.052; Adj. R²=0.05; F =18.63; p <0.0001), for the homeostat (p = 0.0012) and for the circadian (p < 0.0001) coefficients. Conclusion Our results indicate that fluctuations in the dynamics of waking EEG activity are modulated by the circadian and homeostatic processes, although the magnitude of these differences are not underlined by a polymorphism in the clock gene PER3. REFERENCES 1. Cajochen C, Brunner DP, Kräuchi K, Graw P, Wirz-Justice A. Power density in theta/alpha frequencies of the waking EEG progressively increases during sustained wakefulness. Sleep. 1995, 10:890-894. 2. Cajochen C, Wyatt JK, Czeisler CA, Dijk DJ.Separation of circadian and wake duration-dependent modulation of EEG activation during wakefulnessNeuroscience. 2002, 114:1047-60. 3. Viola AU, Archer SN, James LM, Groeger JA, Lo JC, Skene DJ, von Schantz M, Dijk DJ PER3 polymorphism predicts sleep structure and waking performance. Curr Biol 2007,17:613–618. 4. Gillberg M, Kecklund G, Akerstedt T. Relations between performance and subjective rating of sleepiness during a night awake. Sleep 1994, 17:236-241. ACKNOWLEDGEMENTS & SPONSORS Cyclotron Research Centre (CRC) ; Belgian National Funds of Scientific Research (FNRS) ; Actions de Recherche Concertées (ARC, ULg) – Fondation Médicale Reine Elisabeth (FMRE) ; Walloon Excellence in Lifesciences and Biotechnology (WELBIO) ; Wellcome Trust ; Biotechnology and Biological Sciences Research Council (BBSRC) [less ▲]